7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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APC9 2011

York

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Industry ndashled research program funded by EnterpriseIreland which aims to develop a PAT enabled mammalian

cell bioprocess

Modelling andPrediction

ProcessControl

Online

Sampling

AnalyticsSensors

Real timemonitoring

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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X

L

G

V

S in

F

X Biomass

G GlucoseL LactateV Volume

F Feed RateS in Inlet Substrate

Concentration

Process

Controller

Raman Probe

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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ProcessObjective

MaximizeBiomassProductivity

ControlObjective

Maintain a lowGlucoseGlutamine level

in order to avoid a buildup of LactateAmmonia

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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11

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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21

PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

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e n t r a t i o n ( m M )

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P = 40

M = 1

Γ = 1

Λ = 0

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t e ( L h

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n t r a t i o n ( m M )

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001

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0 50 100 150 200 250 300Time (h)

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P = 40

M = 1

Γ = 1

Λ = 10000

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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

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Industry ndashled research program funded by EnterpriseIreland which aims to develop a PAT enabled mammalian

cell bioprocess

Modelling andPrediction

ProcessControl

Online

Sampling

AnalyticsSensors

Real timemonitoring

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X

L

G

V

S in

F

X Biomass

G GlucoseL LactateV Volume

F Feed RateS in Inlet Substrate

Concentration

Process

Controller

Raman Probe

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ProcessObjective

MaximizeBiomassProductivity

ControlObjective

Maintain a lowGlucoseGlutamine level

in order to avoid a buildup of LactateAmmonia

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bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

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Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

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Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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14

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

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983085 983120983113983108 983107983151983150983156983154983151983148

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amp 983124983157983150983141

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983107983151983150983156983154983151983148983148983141983154 983120983141983154983142983151983154983149983137983150983139983141 983123983145983149983157983148983137983156983145983151983150 983122983141983155983157983148983156983155

bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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22

MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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3

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Industry ndashled research program funded by EnterpriseIreland which aims to develop a PAT enabled mammalian

cell bioprocess

Modelling andPrediction

ProcessControl

Online

Sampling

AnalyticsSensors

Real timemonitoring

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983157983150983152983154983141983140983145983139983156983137983138983148983141 983149983137983150983150983141983154

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983158983141983154983161 983140983145983142983142983145983139983157983148983156 983156983151 983139983144983137983154983137983139983156983141983154983145983155983141

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983105983124 983109983150983137983138983148983141983140 983110983141983140983085983138983137983156983139983144 983106983145983151983152983154983151983139983141983155983155

X

L

G

V

S in

F

X Biomass

G GlucoseL LactateV Volume

F Feed RateS in Inlet Substrate

Concentration

Process

Controller

Raman Probe

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983106983145983151983152983154983151983139983141983155983155 983117983151983140983141983148

983125983150983155983156983154983157983139983156983157983154983141983140 983150983151983150983085983155983141983143983154983141983143983137983156983141983140 983138983145983151983152983154983151983139983141983155983155 983149983151983140983141983148

983085 983123983161983155983156983141983149 983151983142 983139983151983157983152983148983141983140 983119983108983109983155 983149983137983155983155 983138983137983148983137983150983139983141 983137983150983140 983154983137983156983141 983141983153983157983137983156983145983151983150983155

983085 983107983151983150983156983137983145983150983155 983137983152983152983154983151983160983145983149983137983156983141983148983161 16 983149983151983140983141983148 983152983137983154983137983149983141983156983141983154983155

983085 983125983155983141983140 983137 983140983145983142983142983141983154983141983150983156983145983137983148 983141983158983151983148983157983156983145983151983150 983152983137983154983137983149983141983156983141983154 983151983152983156983145983149983145983155983137983156983145983151983150983137983148983143983151983154983145983156983144983149 983156983151 983142983145983156 983156983144983141 983152983137983154983137983149983141983156983141983154 983158983137983148983157983141983155 983159983145983156983144 983156983144983141 983152983151983155983155983145983138983148983141 983154983137983150983143983141983155

983139983151983150983155983156983154983137983145983150983141983140 983138983137983155983141983140 983151983150 983152983157983138983148983145983155983144983141983140 983158983137983148983157983141983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7

983120983154983151983139983141983155983155 983107983151983150983156983154983151983148

ProcessObjective

MaximizeBiomassProductivity

ControlObjective

Maintain a lowGlucoseGlutamine level

in order to avoid a buildup of LactateAmmonia

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156

983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156

bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156

Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156

Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150

983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148983148983141983154 983120983141983154983142983151983154983149983137983150983139983141 983123983145983149983157983148983137983156983145983151983150 983122983141983155983157983148983156983155

bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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21

PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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22

MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

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bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

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Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

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X

L

G

V

S in

F

X Biomass

G GlucoseL LactateV Volume

F Feed RateS in Inlet Substrate

Concentration

Process

Controller

Raman Probe

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ProcessObjective

MaximizeBiomassProductivity

ControlObjective

Maintain a lowGlucoseGlutamine level

in order to avoid a buildup of LactateAmmonia

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bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

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Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

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Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

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amp 983124983157983150983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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5

10

15

20

25

30

0 50 100 150 200 250 300

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CglcSet-point

0

001

002

003

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F e e d - r a

t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

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n t r a t i o n ( m M ) Cglc

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F e e d r a

t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

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C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

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F e e d r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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21

PID Disturbance Compensation

0

5

10

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C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

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008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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MPC Disturbance Compensation

0

510

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C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

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01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

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Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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n t r a t i o n ( m M )

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005

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007

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F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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Set-point

0

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004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

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F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0

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Set-point

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001

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004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

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15

20

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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amp 983124983157983150983141

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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X

L

G

V

S in

F

X Biomass

G GlucoseL LactateV Volume

F Feed RateS in Inlet Substrate

Concentration

Process

Controller

Raman Probe

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983106983145983151983152983154983151983139983141983155983155 983117983151983140983141983148

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983154983151983139983141983155983155 983107983151983150983156983154983151983148

ProcessObjective

MaximizeBiomassProductivity

ControlObjective

Maintain a lowGlucoseGlutamine level

in order to avoid a buildup of LactateAmmonia

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

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amp 983124983157983150983141

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156

bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150

983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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21

PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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22

MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

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amp 983124983157983150983141

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983148

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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

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983085 983123983161983155983156983141983149 983151983142 983139983151983157983152983148983141983140 983119983108983109983155 983149983137983155983155 983138983137983148983137983150983139983141 983137983150983140 983154983137983156983141 983141983153983157983137983156983145983151983150983155

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983139983151983150983155983156983154983137983145983150983141983140 983138983137983155983141983140 983151983150 983152983157983138983148983145983155983144983141983140 983158983137983148983157983141983155

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7

983120983154983151983139983141983155983155 983107983151983150983156983154983151983148

ProcessObjective

MaximizeBiomassProductivity

ControlObjective

Maintain a lowGlucoseGlutamine level

in order to avoid a buildup of LactateAmmonia

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983140983141983158983141983148983151983152983149983141983150983156

983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

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bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150

983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

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983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7

983120983154983151983139983141983155983155 983107983151983150983156983154983151983148

ProcessObjective

MaximizeBiomassProductivity

ControlObjective

Maintain a lowGlucoseGlutamine level

in order to avoid a buildup of LactateAmmonia

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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amp 983124983157983150983141

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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9

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bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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11

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

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983085 983120983113983108 983107983151983150983156983154983151983148

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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21

PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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22

MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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8

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amp 983124983157983150983141

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bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

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C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0

5

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30

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e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

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C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0

5

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15

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25

30

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n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983149983151983140983141983148 amp

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983107983151983150983156983154983151983148

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983154983141983137983148983085983156983145983149983141

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983125983123983106983124983141983160983156 983142983145983148983141

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983124983141983160983156 983142983145983148983141

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983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

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983139983151983150983156983154983151983148

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983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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9

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bull Based on the ISA control law consisting of three control

parameters (K Td Ti)

bull Control parameters tuned via Ziegler Nichols (Closedloop) relay based tuning

Classical Control PID Controller

++= int

t

d

i dt

t de

T d eT t eK t u0

)(

)(

1

)()( τ τ

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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11

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983085 983120983113983108 983107983151983150983156983154983151983148

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

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983122983141983137983148

983124983145983149983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

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C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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Set-point

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005

006

007

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F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

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F e e d - r a t e ( L h )

Controller Output

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CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

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CglcSet-point

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0

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

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amp 983124983157983150983141

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983148

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bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

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Setpoint OutputProcess

P

I

D

)(t Ke

int t

i

d eT

K

0)( τ τ

dt

t deKT d

)(

sum sum+

-

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

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Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

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Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

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Controller Output

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PID Disturbance Compensation

0

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n t r a t i o n ( m M ) Cglc

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0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

15

20

25

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C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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0

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0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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F e e d - r a

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Controller Output

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Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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0

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e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

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0

5

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30

0 50 100 150 200 250 300

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C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

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005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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amp 983124983157983150983141

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983119983120983107983119983120983107

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

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bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Classical Control PID Controller Tuning

Ziegler Nichols closed loop with relay identification technique

71

U K PID K =

T i =

T d

=

2

U P

8

U P

= 0010558

= 04

= 01

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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12

Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

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983124983145983149983141

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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0

5

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20

25

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C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

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F e e d - r a

t e ( L h )

Controller Output

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0

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n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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0

5

10

15

20

25

30

0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

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PID Disturbance Compensation

0

5

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25

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C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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0

5

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15

20

25

30

0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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)

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0001002003004005006007

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F e e d - r a t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0

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007

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F e e d - r a

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Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Control Strategy Development

Output

Setpoint

Process

ModelObjectiveFunction

Optimisation

Feed

Advanced Control MPC Controller

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

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F e e d - r a

t e ( L h )

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t e ( L h )

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Set-point

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003

004

005

006

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F e e d r a

t e ( L h )

Controller Output

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PID Disturbance Compensation

0

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002

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01

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Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

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)

CglcSet-point

0

002

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006

008

01

012

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t e ( L h )

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Disturbanceapplied

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005

006

007

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F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

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e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

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amp 983124983157983150983141

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983125983123983106983124983141983160983156 983142983145983148983141

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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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36

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983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

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983139983151983150983156983154983151983148

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983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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13

Control Strategy Development

Industrial MPC Formulation

sumsum =

minus++

=

+

∆∆

Λ∆+minusΓ minus+

M

i

ik ik

P

i

ik t ut u

t ut Rt y M k k 1

2

)1

2

1)()(()()((min

1

Subject to

maxmin

maxmin

uuu

y y y

∆le∆le∆

lele

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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14

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150

983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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16

983107983151983150983156983154983151983148983148983141983154 983120983141983154983142983151983154983149983137983150983139983141 983123983145983149983157983148983137983156983145983151983150 983122983141983155983157983148983156983155

bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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19

983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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21

PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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22

MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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23

983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

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F e e d - r a

t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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Set-point

0

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0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

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P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0

5

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15

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C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

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Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

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0 50 100 150 200 250 300

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C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

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007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

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20

25

30

0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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amp 983124983157983150983141

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Advanced Control MPC Tuning

4 Tuning parameters

P = Prediction horizon

M = Control horizon

Γ = Output weight matrix

Λ = Input weight matrix

Offline Tuning Rules

P = Increase until no further effect

M = 1 (gt1 leads to more aggressive control)

Γ = scale on control variables = 1

Λ = Increase to avoid aggressive CO

Tuning results

P = 10

M = 1

Γ = 1

Λ = 0

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983085 983120983113983108 983107983151983150983156983154983151983148

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

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F e e d - r a

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n t r a t i o n ( m M ) Cglc

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001

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006

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F e e d r a

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Controller Output

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PID Disturbance Compensation

0

5

10

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C o n c e

n t r a t i o n ( m M ) Cglc

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002

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008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

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MPC Disturbance Compensation

0

510

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C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

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01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

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Controller Output

Fast lsquoon-offrsquo

Control

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0

001

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003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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F e e d - r a

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0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

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0

5

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)

CglcSet-point

0001002003004005006007

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F e e d - r a t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

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t e ( L h

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

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003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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amp 983124983157983150983141

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983155983145983149983157983148983137983156983145983151983150

983085 983120983113983108 983107983151983150983156983154983151983148

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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PID Disturbance Compensation

0

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Disturbanceapplied

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MPC Disturbance Compensation

0

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Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

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Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

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F e e d - r a t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

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20

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C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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n t r a t i o n ( m M )

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0

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F e e d - r a

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Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

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25

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0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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amp 983124983157983150983141

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

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983139983151983150983156983154983151983148

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bullSet-point Tracking

bullDisturbance Compensation

bullPropagation of Measurement Noise

Performance Off-Line Testing Criteria

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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PID Disturbance Compensation

0

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Disturbanceapplied

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MPC Disturbance Compensation

0

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983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

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Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

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Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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F e e d - r a

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P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0

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C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

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0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

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007

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F e e d - r a

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Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

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0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

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0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

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983124983145983149983141

983148

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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983149983151983140983141983148 amp

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983125983123983106983124983141983160983156 983142983145983148983141

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15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

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PID Disturbance Compensation

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Disturbanceapplied

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MPC Disturbance Compensation

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Fast lsquoon-offrsquo

Control

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Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

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P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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0001002003004005006007

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CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

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F e e d - r a t e ( L h )

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P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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F e e d - r a

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

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0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

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P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 1839

18

983120983113983108 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

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CglcSet-point

0

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F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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19

983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

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t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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20

983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

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C o n c e

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Set-point

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F e e d r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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21

PID Disturbance Compensation

0

5

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n t r a t i o n ( m M ) Cglc

Set-point

0

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008

01

012

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F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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22

MPC Disturbance Compensation

0

510

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)

CglcSet-point

0

002

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006

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01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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23

983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439

24

983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

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0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

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30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639

26

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739

27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 1939

19

983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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21

PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2339

23

983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439

24

983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539

25

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639

26

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739

27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

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983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983123983152983141983139983156983154983137983148

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983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

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983125983123983106983124983141983160983156 983142983145983148983141

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983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983123983141983156983085983152983151983145983150983156 983123983156983141983152 983124983154983137983139983147983145983150983143

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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21

PID Disturbance Compensation

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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22

MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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23

983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539

25

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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26

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

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983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983120983154983151983138983141

983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

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983105983106983106 983160983120983105983124 983108983137983156983137

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983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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21

PID Disturbance Compensation

0

5

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Time (h)

C o n c e

n t r a t i o n ( m M ) Cglc

Set-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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MPC Disturbance Compensation

0

510

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)

CglcSet-point

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012

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F e e d r a

t e ( L h )

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Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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n t r a t i o n ( m M )

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005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

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e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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Set-point

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007

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F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

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0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

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983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2239

22

MPC Disturbance Compensation

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M

)

CglcSet-point

0

002

004

006

008

01

012

0 50 100 150 200 250 300Time (h)

F e e d r a

t e ( L h )

Controller Output

Disturbanceapplied

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2339

23

983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439

24

983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539

25

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639

26

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739

27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2339

23

983120983113983108 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

Fast lsquoon-offrsquo

Control

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2439

24

983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c

e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539

25

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639

26

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739

27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

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003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983142983145983148983141

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

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983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

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983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

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983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983120983113 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

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e n t r a t i o n ( m M ) Cglc

Set-point

0

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004

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006007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h )

Controller Output

Removal oflsquoDrsquo term leadsto less abruptcontrol

Better set-point tracking

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

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t e ( L h )

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7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

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25

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0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

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983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

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983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2539

25

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639

26

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739

27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2639

26

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

510

15

20

25

30

0 50 100 150 200 250 300Time (h)

C o n c e n t r a t i o n ( m M ) Cglc

Set-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h )

Controller Output

P = 10

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739

27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2739

27

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M

)

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2839

28

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c

e n t r a t i o n ( m M )

CglcSet-point

0001002003004005006007

0 50 100 150 200 250 300

Time (h)

F e e d - r a t e ( L h )

Controller Output

P = 40

M = 1

Γ = 1

Λ = 0

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983120983154983151983138983141

983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 2939

29

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

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15

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0 50 100 150 200 250 300

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C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

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003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a

t e ( L h

Controller Output

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3039

30

983117983120983107 983120983154983151983152983137983143983137983156983145983151983150 983151983142 983117983141983137983155983157983154983141983149983141983150983156 983118983151983145983155983141

0

5

10

15

20

25

30

0 50 100 150 200 250 300

Time (h)

C o n c e

n t r a t i o n ( m M )

CglcSet-point

0

001

002

003

004

005

006

007

0 50 100 150 200 250 300Time (h)

F e e d - r a t e ( L h

Controller Output

P = 40

M = 1

Γ = 1

Λ = 10000

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

983122983141983137983148

983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

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983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

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983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

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983124983141983160983156 983142983145983148983141

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983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3139

31

983123983145983149983157983148983137983156983145983151983150 983123983156983157983140983161 983122983141983155983157983148983156983155

bull Reference tracking MPC starts adjusting the control signalahead of reference changes while PID cannot start beforeMPC gives less control error

bull Disturbance compensation MPC better than PID MPCcan deal with plant-model mismatch

bull Measurement noise Less propagation through tuned MPCthan tuned PID By increasing the penalty weight on the input

the control action in the presence of measurement noise canbe dampened to a more smooth control signal

bullSISOMIMO PID can only handle one input and one output

MPC is a multivariable control strategy

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

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983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983142983145983148983141

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

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983110983141983141983140 983120983157983149983152

983125983123983106983124983141983160983156 983142983145983148983141

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983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

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983124983141983160983156 983142983145983148983141

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983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983120983154983151983138983141

983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3239

32

983107983151983150983156983154983151983148 983123983156983154983137983156983141983143983161 983108983141983158983141983148983151983152983149983141983150983156 983123983145983149983157983148983137983156983145983151983150 amp 983105983152983152983148983145983139983137983156983145983151983150

983107983151983150983156983154983151983148 983155983156983154983137983156983141983143983161 983154983141983137983148 983156983145983149983141 983137983152983152983148983145983139983137983156983145983151983150983085 983120983113983108 983107983151983150983156983154983151983148

983085 983118983151983150983085983148983145983150983141983137983154 983117983120983107 (983117983151983140983141983148 983120983154983141983140983145983139983156983145983158983141 983107983151983150983156983154983151983148)

983107983151983150983142983145983143983157983154983141

amp 983124983157983150983141

983123983145983149983157983148983137983156983141

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983124983145983149983141

983148

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

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3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

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983110983141983141983140 983120983157983149983152

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983110983145983148983141 983108983145983154983141983139983156983151983154983161

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983124983141983160983156 983142983145983148983141

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983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

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983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3339

33

3 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983148983148 983105 983148983145 983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

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983124983141983160983156 983142983145983148983141

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983124983141983160983156 983142983145983148983141

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983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3439

34

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983110983141983141983140 983120983157983149983152

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983154983141983137983140983159983154983145983156983141

983110983145983148983141 983108983145983154983141983139983156983151983154983161

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983124983141983160983156 983142983145983148983141

983154983141983137983140983159983154983145983156983141

983123983141983154983145983137983148

15 983116 983106983145 983156 983109 983145 983156 983148 983123 983156

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

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983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3539

35

15 983116 983106983145983151983154983141983137983139983156983151983154 983109983160983152983141983154983145983149983141983150983156983137983148 983123983141983156983085983157983152

983122 983148 983124983145 983107 983156 983148983148 983105 983148983145 983156983145

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3639

36

983122983141983137983148 983124983145983149983141 983107983151983150983156983154983151983148983148983141983154 983105983152983152983148983145983139983137983156983145983151983150

983122983137983149983137983150

983120983154983151983138983141

983123983152983141983139983156983154983137983148

983137983139983153983157983145983155983145983156983145983151983150

983155983151983142983156983159983137983154983141

983123983152983141983139983156983154983137983148

983142983145983148983141

983107983137983148983145983138983154983137983156983145983151983150

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141 983141983150983143983145983150983141

983107983151983150983156983154983151983148

983149983151983140983141983148 amp

983154983141983137983148983085983156983145983149983141

983141983150983143983145983150983141

983105983106983106

98309600983160983137

983139983151983150983156983154983151983148

983155983161983155983156983141983149

983125983123983106 983124983107983120983113983120

983105983106983106 983160983120983105983124 983108983137983156983137

983117983137983150983137983143983141983154

983119983120983107983119983120983107

983119983120983107

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3739

37

983109983160983152983141983154983145983149983141983150983156983137983148 983122983141983155983157983148983156983155

bull Communication and controller configuration for real timeapplication complete

bull Plan to run MPC and PID control on both the 3 L and 15 Lbioreactor setups with the Raman probe for real time monitoring ofglucose concentration

bullIn the next few weeks preliminary experimental data for the closedloop feedback control fed-batch runs will be gathered

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3839

38

983107983151983150983139983148983157983155983145983151983150983155 983137983150983140 983110983157983156983157983154983141 983127983151983154983147

bull Fed-batch model has been incorporated into the simulation ofPID and MPC controller technologies

bull MPC performed best for set-point tracking both in thepresence of noise and disturbances from the simulation study

bull Configured and simulated control strategies are to be appliedin real time with online and at-line PAT on two differentbioreactor scales

bull Real time results are to be compared to the results gatheredon a simulation basis

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland

7232019 Mon 1000 Comparison of Controller Technologies for Fed Batch Fermentation S Craven

httpslidepdfcomreaderfullmon-1000-comparison-of-controller-technologies-for-fed-batch-fermentation 3939

39

983105983139983147983150983151983159983148983141983140983143983141983149983141983150983156983155

Prof Brian Glennon

Dr Jessica Whelan

PAT-Bio Research Team

Enterprise Ireland